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- W4313430456 abstract "The combustion quality determination in power station boilers is of great importance to avoid air pollution. Complete combustion minimizes the exit of NOx, SOx, CO, and CO2 emissions, also ensuring the consistency in load generation in thermal power plants. This chapter proposes a novel hybrid algorithm, called black widow optimization algorithm with mayfly optimization algorithm (BWO-MA), for solving global optimization problems. In this chapter, an effort is made to develop BWO-MA with artificial neural networks (ANN)-based diagnostic model for onset detection of incomplete combustion. Comparison has been done with existing machine learning methods with the proposed BWO-MA-based ANN architecture to accommodate the greater performance. The comprehensive analysis showed that the proposed achieved splendid state-of-the-art performance." @default.
- W4313430456 created "2023-01-06" @default.
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- W4313430456 date "2022-12-19" @default.
- W4313430456 modified "2023-10-15" @default.
- W4313430456 title "Deep Learning Neural Networks for Online Monitoring of the Combustion Process From Flame Colour in Thermal Power Plants" @default.
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- W4313430456 doi "https://doi.org/10.4018/978-1-6684-6275-1.ch011" @default.
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